Land management shapes drought responses of dominant soil microbial taxa across grasslands

Soil microbial communities are dominated by a relatively small number of taxa that may play outsized roles in ecosystem functioning, yet little is known about their capacities to resist and recover from climate extremes such as drought, or how environmental context mediates those responses. Here, we imposed an in situ experimental drought across 30 diverse UK grassland sites with contrasting management intensities and found that: (1) the majority of dominant bacterial (85%) and fungal (89%) taxa exhibit resistant or opportunistic drought strategies, possibly contributing to their ubiquity and dominance across sites; and (2) intensive grassland management decreases the proportion of drought-sensitive and non-resilient dominant bacteria—likely via alleviation of nutrient limitation and pH-related stress under fertilisation and liming—but has the opposite impact on dominant fungi. Our results suggest a potential mechanism by which intensive management promotes bacteria over fungi under drought with implications for soil functioning.


Reviewers' Comments:
Reviewer #1: Remarks to the Author: I thoroughly enjoyed reviewing this manuscript.The authors did an excellent job with the writing.It is the most well-written manuscript I have reviewed.The authors provided a generally comprehensive description of the work.I appreciate the reasoning for the focus on dominant taxa.The takeaway that most of the dominant taxa from these soils exhibit resistant or opportunistic strategies in response to drought provides a foundation for some important theories in soil microbial ecology that have been hinted at in the literature for some time, but scarcely explicitly tested as the authors have done so here.I think this paper will help motivate other researchers in this field to make more of a point of differentiating between dominant and rare taxa and their respective roles in microbial processes and ecosystem functioning.I also appreciate the latitudinal gradient of the experimental design, which strengthens the inference power of these results and--as the authors state--make them more ecologically relevant.
I have provided minor comments in the attached word document with track changes, most of which are suggesting clarifications with phrasing or providing more detail.In particular, I would really like to see broader context added to the hypotheses and to expand on this in the Discussion.With papers like this that focus on soil microbial taxonomic composition, it's important to relay to the reader how microbial composition may influence ecosystem function.The authors have done a nice job with providing possible explanations for microbial responses to drought, land management, etc.Now they just need to bookend the story by providing some thoughts on how these microbial response strategies may affect larger scale ecosystem functions.I think the importance of this work would come through even more by making these small improvements.organic matter decomposition, and pathogen control [1][2][3] , but their functioning can be impacted by climate extremes 4,5 which are becoming increasingly common.Recent evidence shows that despite very high diversity of soil microbial taxa, a small proportion can be considered dominant, i.e., they are found across most soils and are highly abundant relative to other taxa 6,7 .These dominant taxa may be drivers of ecosystem responses to climate extremes (i.e., the mass-ratio hypothesis; Grime, 1998; de Vries et al., 2018), an idea supported by studies of plant communities linking ecosystem responses to the abundances of dominant plant species 10,11 .
Therefore, understanding how dominant microbial taxa respond to climate extremes and how these responses are shaped by environmental factors and land management, will enable better predictions of ecosystem behaviour into the future 12,13 .
Soil microbial taxa can be categorised by life history strategies 14,15 to inform on their capacity to resist and recover from climate extremes such as drought 12,16 .These life history strategies are thought to emerge from correlated sets of traits (e.g., related to resource acquisition, growth yield, and stress tolerance), which are favoured under different environmental conditions 15 .For example, soil microbial communities subjected to moisture pulses had greater proportions of taxa exhibiting a stress-resistant strategy, whereas those under ambient conditions had higher abundances of drought-sensitive taxa 14 .Land management may also shift microbial life history strategies by changing resource availability and plant communities -environmental factors known to shape microbial community structure and function [17][18][19][20][21][22] .However, the interacting effects of land management and climate extremes such as drought have not been studied in the context of microbial life history strategies.This is a necessary step towards using ecological knowledge of soil microbes to predict and understand the consequences of land management decisions on soil functioning and sustainability in the face of climate change.
Here, we carried out a large-scale field experiment across a broad range of grassland sites to explore how the relative abundances of dominant microbial taxa with different droughtresponse strategies are shaped by soil conditions, climate, and land management intensity.We imposed a simulated drought on 15 pairs of grasslands under contrasting management (i.e., intensive and extensive) in three geographically distinct regions of the UK representing a range of soil and climatic conditions (Fig. S1, Table S1).Using an operational approach, we identified dominant microbial taxa and classified them into three broad drought-response strategies (i.e., resi st ant , opport uni st i c, or sensi t i ve) 1 4 .We exami ned t he i nt eract i ng effect s of cl i mat e, soi l proper t i es, and hi st or i cal grassl and management on domi nant mi cr obi al r esponses t axa by dr ought -r esponse st r at egy at t wo t i mepoi nt simmediately following the drought and after a 60-day post-drought period 23 -to capture microbial resistance and resilience to drought 24 .
We hypothesised that: (1) dominant soil microbial taxa largely display resistant or opportunistic strategies under drought, because a capacity to withstand variable moisture conditions would partly explain their ubiquity and abundance across sites; (2) intensive grassland management, characterized by regular fertiliser and lime application and higher plant productivity (Table S1), favours taxa that are maladapted to low resource availability and stress, and therefore will be sensitive to drought; and (3) intensive grassland management favours Commented [BKK2]: Even though you do so in the Methods, it would be helpful to briefly define the strategies here.I think's it's also worth explicitly differentiating between resistant and resilient because many people outside of this literature often use them interchangeably.

Commented [BKK3]:
It would be helpful to add broader context to the hypotheses.What would each of these hypotheses, or them collectively, indicate about microbial function under climate extremes if they were supported?microbial taxa that recover after drought (i.e., resilient), because more favourable soil conditions allow drought-affected taxa to rebound quickly with rewetting.

RESULTS
We found that a relatively small number of bacteria and fungi dominate soils across the grassland sites, and that these taxa were highly resistant to an imposed drought event.For bacteria, dominant taxa (defined as present across all 15 sites and in the top 10 % of relative abundance ranked by 16S rRNA reads 7 ) represented 1269 out of 19224 total operational taxonomic units (OTUs), which accounted for approximately 7 % of total OTUs but 76 % of all reads.For fungi, dominant taxa (present across all three regions and in the top 10 % by ITS rRNA reads) made up 209 out of 12837 total OTUs, accounting for approximately 2 % of total OTUs but 53 % of all reads.Overall, the majority of dominant bacterial (66 %) and fungal (64 %) taxa were classified as displaying a resistant drought strategy, as they showed no response to drought in our hierarchical model using all data across sites and management regimes immediately after the simulated drought (Table S2).Opportunistic taxa, whose relative abundances increased in response to drought, represented 19 % of dominant bacteria and 25 % of dominant fungi; sensitive taxa, whose relative abundances decreased with drought, represented 12 % of dominant bacteria and 7 % of dominant fungi.Figure 1.Dominant bacterial (a) and fungal (b) community responses to drought immediately following drought ("resistance") and after the 60-day post-drought period ("resilience"), limited to the top 500 most abundant taxa across all samples for readability.The inner ring shows the taxonomic tree, coloured by phylum.The middle ring displays drought response strategies ("resistance", immediately following drought) of each OTU (light blue = tolerant resistant, black = opportunistic, pink = sensitive).The outer ring displays responses after the 60-day post drought period ("resilience"; green = resilient taxa that recovered to control levels, dark grey = not resilient).Taxa defined as resistant to the drought (light blue, inner ring) were not tested for resilience.For further information on the identities of all OTUs, see Supplemental Note 2. Dominant bacterial phyla in our dataset comprised primarily (by reads) Proteobacteria (32 %), Acidobacteria (21 %), Verrucomicrobia (13 %), Bacteroidetes (11 %), Firmicutes (9 %), Actinobacteria (7 %), Chloroflexi (3 %), and several other globally distributed taxa.Of these phyla, most contained taxa representing each of the three drought-response strategies (Fig. 1).Glomeromycota tended to display resistant or sensitive drought-response strategies, with only one or no taxa identified as opportunistic in each phylum (Fig. 1).Overall, dominant taxa resistant to drought belonged to different taxonomic groups dispersed across every major lineage of the phylogeny, suggesting that this capability is not limited to specific phylogenetic groups of microbes.
Commented [BKK5]: I would appreciate an Excel table of all dominant taxa, their full taxonomy, and response strategy.It's fine to not provide all this detail in the manuscript, but I think it should be made available.I'm curious (and I'm sure many other readers will be, too) to know which orders, families, etc. have resistant and sensitive taxa.We used structural equation models to infer potential mechanisms through which grassland management affected opportunistic, sensitive, and resistant dominant microbial taxa across sites (Fig. 2).Except for sensitive bacterial taxa, intensive management increased the relative abundances of all dominant microbial drought-response groups.Opportunistic and resistant bacterial taxa were positively impacted by intensive management at both timepoints (both directly and via increased pH; Fig. 2a, b), while sensitive bacterial taxa were either We used structural equation models to infer potential mechanisms through which grassland management affected opportunistic, sensitive, and resistant dominant microbial taxa across sites (Fig. 2).Except for sensitive bacterial taxa, intensive management increased the relative abundances of all dominant microbial drought-response groups.Opportunistic and resistant bacterial taxa were positively impacted by intensive management at both timepoints (both directly and via increased pH; Fig. 2a, b), while sensitive bacterial taxa were either unaffected (following drought) or negatively affected (after the recovery period).Opportunistic and resistant fungal taxa were also positively affected by intensive management (either directly or via increased pH; Fig. 2c, d), but in contrast to sensitive bacterial taxa, sensitive fungal taxa were positively and directly affected by intensive management at both timepoints.As a result, the ratio of opportunistic:sensitive dominant taxa increased under intensive management for bacteria but decreased for fungi (Fig. 3a).Fig. 3. Ratios of the standardized relative abundances of opportunistic:sensitive dominant taxa (a) and resilient:not resilient dominant taxa (b) by grassland management, with bacteria on left and fungi on right.Resilient taxa were defined as having similar relative abundances to those in control plots after the 60-day post-drought recovery period.Ratios were higher for bacteria but lower for fungi in intensively managed grasslands based on generalized linear mixed models using data from control plots across both timepoints (p < 0.05, indicated by *).
Of the environmental variables we considered in the SEMs (total C and N, temperature, texture, moisture, and pH), pH played the most important role.There were strong positive indirect effects of management intensity via increased soil pH for opportunistic and resistant bacterial taxa at both timepoints (Fig. 2a, b).Further investigation revealed unimodal relationships between pH and resistant and resilient bacterial taxa that peaked ca.pH 5.7 (Fig. S4).Fungal taxa were less impacted by pH overall, but there was a positive effect on opportunistic fungal taxa after the drought (Fig. 2c), and a negative effect on resistant fungal taxa after the recovery period (Fig. 2d).While the inclusion of pH did account for one mechanism by which management impacts microbial taxa, the fact that direct paths from the management variable manifested in the SEMs indicates that other mechanisms related to management (and not captured by total soil C and N, soil temperature, texture, and soil water content) are also impacting dominant microbial taxa in these soils.Intensive management did impact other key variables including above-ground plant biomass and plant-available N (Fig. 3) that are implicitly represented by our management variable in the SEM.In general, dominant fungal groups were impacted more strongly by the management variable in our SEMs, while dominant bacterial groups were impacted more strongly by pH and other soil characteristics (total soil C and N, soil temperature, texture, and soil water content).Drought treatment was the best predictor of soil moisture immediately after the simulated drought (day 0), with latitude and soil properties captured in the composite soil variable (total C and N, temperature, texture) also playing important roles (Fig. 2a, c).The drought treatment effect on the different microbial drought-response strategy groups was not fully captured by the field measurements of soil moisture -which only provided a snapshot of soil moisture conditions at the time of sampling -indicated by the direct paths from drought treatment for several microbial groups at that timepoint at day 0 (Fig. 2a, c).After the 60-day post-drought period, the drought treatment no longer predicted soil moisture or microbial drought-response strategy groups.Instead, latitude was a very strong predictor of soil moisture, and soil properties (composite soil variable) were an important predictor for bacterial drought response groups, but not fungal drought response groups (Fig. 2b, d).
The absence of drought treatment effects on sensitive and opportunistic bacterial or fungal taxa after the 60-day post-drought period indicates group-level recovery within that time (Fig. 2b, d).We also categorized individual opportunistic and sensitive dominant taxa as resilient or not based on their abundances relative to control plots after the 60-day post-drought recovery period.While most of the 503 drought-affected (opportunistic or sensitive) taxa were found to be resilient after 60 days, we identified 110 taxa that were not (Fig. 1).Of these, 34 were sensitive bacterial taxa and 8 were sensitive fungal taxa that did not return to control plot levels after the 60-day post-drought recovery period.Analyses of resilient bacterial and fungal taxa groups in control plots across both timepoints revealed that the relative proportion of resilient taxa (ratio of resilient:not resilient taxa; Fig. 3b) was higher for bacteria but lower for fungi under intensive compared to extensive grassland management.

DISCUSSION
Our study provides novel evidence, from a broad range of grassland sites varying in climatic and soil conditions (Table S1), that dominant soil microbial taxa are highly resistant to drought.Despite significant and sizable reductions in soil moisture under experimental drought across sites within three geographically distinct regions of the UK (Fig. S2), the majority of dominant soil microbial taxa either did not respond or responded positively, consistent with our first hypothesis.Of the taxa that were negatively impacted by the drought treatment (droughtsensitive strategies), the majority were resilient (i.e., fully recovered to control levels within the 60-day post-drought period).The resistance and resilience of these soil microbial taxa to drought, observed here across three geographically distinct regions of the UK, may in part explain why they are present and highly abundant (i.e., dominant) across sites 7 .The use of a distributed landscape design combined with an in situ experimental drought treatment uniquely demonstrates that responses of dominant soil microbial to drought are consistent at a large spatial scale.Though drought severity can be difficult to quantify 25 , especially at the microscale most relevant to microbiota 26 , we observed significant effects of the drought treatment on ecosystem respiration and microbial community structure (including non-dominant taxa) at the plot scale across all regions, indicating that our drought treatment was ecologically significant (Fig. S2, Fig. S3, Table S3).Our findings align with recent studies showing that abundant microbial taxa are more resistant to perturbations 27 , are adapted to broader ranges of environmental conditions 28,29 , and display higher frequencies of genomic traits associated with stress-tolerance and competitive abilities 6 than rare microbial taxa.These results suggest that dominant microbial taxa in grassland soils are generalists adapted to varying environmental conditions, allowing them to withstand perturbations and thrive across a broad range of sites.
We found that environmental context and land management did affect the relative abundances of dominant microbial taxa with different drought response strategies, but not in ways we expected.We hypothesised that the impacts of grassland management on the resistance and resilience (i.e., the capacity to recover) of dominant microbial taxa to drought would be inversely related, and that bacterial and fungal communities would respond similarly.More specifically we hypothesised that microbial communities in intensively managed grasslands would be more sensitive to drought due to lower stress-tolerance but be more resilient due to higher available nutrients and more ideal pH levels enabling recovery.However, our findings suggest that resistance and resilience of dominant soil microbial taxa are positively related in the context of grassland management, and that bacterial and fungal communities respond to intensive and extensive grassland management in divergent ways.Compared to communities under extensive management, dominant bacterial communities under intensive management shifted toward less sensitive and more resilient drought strategies, while dominant fungal communities shifted toward more sensitive and less resilient drought strategies (Fig. 3).This suggests that across these grassland sites, dominant bacterial communities under more intensive management are better able to withstand and recover from drought than those under extensive management, while dominant fungal communities are not.Again, these findings were apparent when data were aggregated across all three UK regions, which cover a broad range of climatic and soil conditions.
The divergence between bacterial and fungal responses to more intensive management may be explained by differences in their sensitivities to prevailing conditions including pH, nutrients, and plant productivity.The intensively managed grasslands used in our study all receive regular inputs of inorganic fertilisers to reduce nutrient limitation along with lime, which increases pH toward neutral levels and leads to increased plant productivity (Fig. 4).For the dominant bacterial communities at these sites, liming likely alleviates pH-related stress, allowing opportunistic taxa to succeed under the drought treatment relative to others taxa under the drought treatment.These opportunistic taxa may have traits related to high growth yields or efficient resource acquisition 30 that enable them to take rapid advantage of abundant resources under changing conditions.Indeed, the higher soil pH observed in the intensively managed grasslands (due to lime application) positively affected resistant and resilient bacterial taxa relative to the extensive grasslands with more acidic soils (Fig. S4).This finding agrees with previous work on similar soils suggesting that relief from acidic conditions allows bacterial communities to shift from maintenance to growth strategies 31 .In that study, the key pH threshold for shifts in microbial strategies was found to be pH ~ 6.2, however, in our study the pH in intensively managed fields rarely surpassed that threshold, suggesting the pH threshold could be lower for many of our sites.In addition to higher pH, the higher soil nutrient availability and plant productivity in the intensively managed grasslands likely further favoured copiotrophic or high-yield bacterial taxa 32 capable of taking advantage of changing conditions under drought, or capitalizing on flushes of nutrients upon rewetting of the droughted plots 30,33 .
Indeed, Actinobacteria had the highest proportion of opportunistic taxa in our study (consistent with a previous large-scale study of drought effects on microbial communities in grasslands 4 ) and this phylum is thought to comprise primarily copiotrophs or high-yield strategy taxa favoured by N additions 21,32,34,35 .Further, Verrucomicrobia and Acidobacteria, which that are thought to be comprised of mainly oligotrophs 21,34,35 , had the lowest proportions of droughtsensitive taxa that were resilient.
In contrast to dominant bacterial communities, dominant fungal communities under more intensive management generally displayed lower resistance and resilience to drought than in extensively managed grasslands.Fungal communities are known to be less sensitive to pH than bacteria 36 , and we didn't observe strong pH effects on resistant or resilient dominant fungal taxa in this study (Fig. S4), suggesting that alleviation of pH-related stress was not as relevant a mechanism for fungi in this case.Instead, other local-scale impacts of management such as increased plant biomass and available nutrients (Fig. 4) were the likely drivers of fungal responses, as suggested by the fact that the management variable in our SEMs generally affected dominant fungal groups more strongly than pH or prevailing soil conditions (Fig. 2).Fungal communities have been shown to respond strongly to fertilisation 21,37 and are often suppressed relative to bacteria under more intensive grassland management 18,38,39 , consistent with our observation of lower fungal:bacterial ratios under intensive compared to extensive management across sites (Fig 4).Furthermore, we recently showed in a sub-set of the grassland sites studied

Commented [BKK6]:
It would helpful to add in parentheses a brief description of oligotrophs as they relate to copiotrophs.Ex: generally have a slow growth strategy and thrive in nutrient-poor conditions here that intensive management reduces the flux of recent photosynthate to soil food webs including arbuscular mycorrhizal fungi, indicating importance of this pathway for driving fungal activity 40 .It is therefore possible that this pathway of reduced energy flux could contribute to the increased sensitivity of dominant fungal communities to drought (which further reduces the flux of recent photosynthate below-ground 41 ) in intensively managed grasslands.The opposing responses of dominant bacteria and fungi to grassland management in terms of their resistance and resilience to drought may help to explain widespread observations of increasing bacterial:fungal biomass ratios with grassland intensification 18,39,42 .
Overall, the alignment of resistance and resilience in the context of grassland management intensity for both bacteria and fungi was unexpected, as other studies have found observed trade-offs between resistance and resilience in soil microbial communities [43][44][45] .
However, in our study encompassing a relatively broad range of soils, pH was an important driver of both resistance and resilience in dominant bacterial communities, while fertilisation may have driven both resistance and resilience of dominant fungal communities, which would help to explain the alignment in both responses with management.While consistencies in taxonlevel responses to separate drought and nitrogen addition treatments has been observed previously 46 , the sets of traits determining responses to soil water availability versus nutrient availability or pH may not always align and a multi-dimensional framework may be necessary for considering microbial life history strategies 47 and predicting microbial responses to climate extremes.
We observed contrasting phylum-level responses to drought in soil dominant bacterial and fungal communities, suggesting that certain phyla may be inherently more resistant and resilient to drought than others.Actinobacteria contained a high proportion of resistant and opportunistic taxa, with only one taxon identified as sensitive, consistent with previous observations that Actinobacteria are prevalent in dry environments 48 and are highly resistant or increase in response to drought 4,47 .Members of Firmicutes and Bacteroidetes were generally more sensitive to the drought treatment, and while members of Bacteroidetes have been shown to decrease in relative abundance in drier soils, members of Firmicutes have previously shown the opposite response 49 .It is possible that these previous observations may have been driven primarily by one or a few taxa, which may not have been present (or defined as dominant) here.

Context-dependent drought responses have been previously observed for other phyla including
Commented [BKK7]: These ratios are usually expressed as fungi:bacteria.
Proteobacteria and Planctomycetes 49 , and we also observed relatively high numbers of taxa with different drought-response strategies in those phyla.
Dominant members of Ascomycota were particularly opportunistic under drought, which agrees with findings that Ascomycota are dominant globally and are generalists that are adapted to a wide range of conditions 6,48 .Within Glomeromycota, dominant taxa that responded to our drought treatment were sensitive, in agreement previous findings that both community composition 4 and functionality 50,51 of this group of fungi respond to drought in other systems.
However, the majority of dominant Glomeromycota in this study were found to be resistant to the drought, suggesting that the results from these other studies my largely be driven by only a few dominant members of Glomeromycota, or by taxa that were not defined as dominant here.
Two members of Basidiomycota indicated sensitivity to drought, and one taxon did not recover after the 60-day post-drought period.Given that Basidiomycota are important decomposers and ectomycorrhizal symbionts in forests 52 , microbial communities in forested systems (or under forest expansion) may be sensitive to drought with potential implications for forest growth and ecosystem functioning 53 , which deserves further study.
Overall, our findings from a broad range of grassland sites across the UK indicate that most the majority of the dominant soil microbial taxa are highly resistant to drought, which may explain their prevalence across a diverse range of grassland soils.We further show that grassland management, along with climate and soil properties, shapes the relative abundances of dominant soil microbial taxa with differing drought-response strategies.More intensive grassland management, which creates more optimal pH and higher nitrogen availability compared to extensive management, promoted opportunistic and resilient bacterial taxa that may employ copiotrophic or fast-response strategies and are able to take advantage of changing conditions.
However, it has the opposite effect on dominant fungal taxa which may help to explain increases in bacterial prevalence over fungi with grassland intensification 18,39,42,54 .By demonstrating that land management shapes the drought-response strategies of dominant microbial taxa across grasslands, our findings improve our understanding of how soil microbial communities respond to drought.Moreover, by identifying consistent management-and drought-induced responses of dominant microbial taxa, our findings pave the way for future studies that interrogate their functional attributes and links to key ecosystem functions 55 .Given the enormous complexity of soil microbial communities and their dynamics in space and time, our approach of focusing on Commented [BKK8]: You've done a great job with the discussion, and the cherry on top would be to expand on this sentence a bit more-like I suggested in the hypotheses section of the Introduction.
Just providing a few sentences about how these microbial strategy responses to drought and land management may impact particular ecosystem functions like carbon, nutrient cycling, etc.This would really help drive home the importance of this work.
the drought response strategies of dominant taxa is one way to make this task more feasible in the future.

Field sites
The field experiment was carried out between May and September of 2016 across a series of mesotrophic grasslands in Great Britain, concentrated in three regions: Devon in southwest England, North Yorkshire in northern England, and Aberdeenshire in northeast Scotland (Fig. S1, Table S1).Prior to the start of the experiment, we identified 15 pairs of fields on working farms with contrasting management and classified them as either intensively or extensively managed based on observations of plant communities and interviews with farmers and land managers.Extensively managed fields received very low or no synthetic fertiliser and lime, had more diverse plant communities, were generally not cut for hay or silage, and were grazed at low stocking densities by sheep or cattle.Intensively managed fields received regular applications of fertiliser and lime (as deemed necessary by the farmer), had less diverse plant species mixtures, were cut for hay or silage, and were grazed at higher stocking densities.Differences in management had been maintained for at least 10 years, and typically longer (Table S1).
Wherever possible, we identified paired intensive and extensive fields that were adjacent, to minimize differences in intrinsic environmental variables such as topography, weather patterns, and soil type.If fields were not immediately adjacent, we chose fields no more than 0.5 km apart and used farmer and land manager interviews to ensure minimal differences between paired fields aside from management.

Experimental design
This study employed a randomized complete block design with subsampling.In each region, 5 sites were identified that each had two differently managed fields within 0.5 km for a total of 15 sites and 30 paired fields.In each of the 30 fields, three pairs of drought and control plots were established and enclosed in fencing for protection from large mammals and machinery.A field drought was simulated by placing a transparent roof (1.5 m * 1.3 m) on each drought plot alongside its paired delimited control plot for 60 days between May and July of 2016, which equates to a greater than 100-year drought for these sites 56 .In total, there were 90 droughtcontrol pairs, and the three within-field replicates were treated appropriately in all statistical models by either including site and field as random effects or by aggregating the data at the field scale where random effects could not be modelled.At the end of the drought period, drought shelters were removed and an initial ("day 0") sampling and measurement of soil functions was carried out to assess the impact of the drought.Sampling and measurement were done in the centre of the plots, leaving a 15 cm buffer to minimize edge effects.Immediately following this sampling event, droughted plots were watered (amounts were based on average July rain events from 2007-2011 for the nearest Met Office from each region 57 ) to stimulate the start of the post-drought period.Sampling was repeated 60 days after the removal of the shelters to capture recovery during the post-drought period.

Soil sampling
At all timepoints, multiple soil samples were collected to 10 cm depth and composited for measurements of soil nematode communities (6 * 1.3-cm diameter cores) soil microarthropod communities (4 * 2.5-cm diameter cores), and soil microbiota and chemical analysis (3 * 2.5-cm diameter cores).Soil samples were immediately composited in plastic sample bags and transferred to coolers for transport to laboratories within 24-48 hours.Samples intended for soil fauna analysis were kept open to allow for gas exchange.At each sampling event, soil moisture and temperature were measured using Wet Sensor probes (WET-2, Delta-T Devices, Cambridge, UK).Bulk density was measured using the core technique at the time of the drought treatment establishment, using one core per plot for a total of 6 cores per field, and the average value for each field was used throughout the study.

Soil biogeochemical analysis
Samples for analysis of microbial communities, texture, and C and N analyses were transported to the University of Manchester and stored at 4°C for a maximum of 3 days until further processing and analysis.All samples were sieved to 4 mm for homogenization and removal of visible plant material and rocks, after which samples were divided for further analyses.One subsample was immediately frozen at -80°C awaiting microbial DNA sequencing.A second subsample was weighed, placed in a paper bag, and dried to constant weight at 40°C to calculate soil moisture.This subsample was used for further analyses of total C and N concentrations using a Vario Cube (Elementar Americas Inc., Ronkonkoma, NY, USA), and soil texture analysis by laser granulometry using a Malvern Mastersizer 2000 (Malvern Instruments Ltd, Malvern, Worcestershire, UK) following removal of OM with H2O2 at 50 °C overnight.Soil pH was measured on field moist subsamples in slurries of 1:2.5 soil:deionized water using a pH meter (Seven2GO Mettler Toledo, Columbus, Ohio, USA).Further analyses are described in Supplemental Methods.

16S and ITS amplicon sequencing and data analysis
Amplicon sequencing and bioinformatic and statistical analyses of sequencing data were done following the methods of De Vries et al. 9 .DNA was extracted from 0.16 g of soil using the MoBIO PowerSoil-htp 96-Well DNA Isolation kit (Carlsbad, CA, USA) according to the manufacturer's protocols and the DNA quality was checked by agarose gel electrophoresis.Bacterial 16S rRNA sequencing followed the dual indexing protocol of Kozich et al. (2013) for the MiSeq plaform (Illumina, San Diego, CA, USA).Each primer consisted of the appropriate Illumina adapter, 8-nt index sequence, a 10-nt pad sequence, a 2-nt linker, and the amplicon specific primer.The V3-V4 hypervariable regions of the bacterial 16S rRNA gene were amplified using primers 341F 59 and 806R 60 , CCTACGGGAGGCAGCAG, and GCTATTGGAGCTGGAATTAC, respectively.Amplicons were generated using high-fidelity DNA polymerase Q5 Taq (New England Biolabs, Ipswich, USA).After an initial denaturation at 95 °C for 2 minutes, PCR conditions were: denaturation at 95 °C for 15 seconds, annealing at 55 °C for 30 seconds with extension at 72 °C for 30 seconds, repeated for 30 cycles, followed by a final extension of 10 minutes at 72 °C.Fungal internal transcribed spacer (ITS) amplicon sequences were generated using a 2-step amplification approach.Primers GTGARTCATCGAATCTTTG and TCCTCCGCTTATTGATATGC 61 were each modified at the 5' end with the addition of Illumina pre-adapter and Nextera sequencing primer sequences.After an initial denaturation at 95°C for 2 minutes, PCR conditions were: denaturation at 95°C for 15 seconds, annealing at 52°C for 30 seconds with extension at 72°C for 30 seconds, repeated for 25 cycles, with a final extension of 10 minutes at 72°C included.Sequenced paired-end reads were joined using PEAR (Zhang et al., 2014), quality filtered using FASTX tools (hannonlab.cshl.edu),and length-filtered to a minimum length of 300 bp.The presence of PhiX and adaptors were checked for and removed with BBTools (jgi.doe.gov/data-and-tools/bbtools/), and chimeras were identified and removed with VSEARCH_UCHIME_REF 62 using Greengenes Release 13_5 (at 97%).Singletons were removed and the resulting sequences were clustered into operational taxonomic units (OTUs) with VSEARCH_CLUSTER 62 at 97% sequence identity.Representative sequences for each OTU were taxonomically assigned by RDP Classifier with the bootstrap threshold of 0.8 or greater using the Greengenes Release 13_5 (full) as the reference.Unless stated otherwise, default parameters were used for all steps listed.The fungal ITS sequences were analysed using PIPITS 63 with default parameters.Briefly, this involved quality filtering and 97% clustering of the ITS2 region as indicated above for the 16S processing, using the UNITE database for chimera removal and taxonomic identification of representative OTUs.Both bacterial and fungal OTU abundance tables were resampled to a minimum of 9000 reads per sample, and samples with zero reads were removed prior to further analyses.

Statistical analysis
All analyses were done separately for bacterial and fungal taxa in R version 4.0.2 64.We defined dominant taxa as those which were present across all 15 sites (management pairs) and represented the top 10% of taxa when ranked by relative abundance (rRNA reads).The responses of these dominant taxa to drought treatment were tested using generalized linear mixed models across all experimental plot pairs with drought treatment as a fixed effect, and region/site/field as nested random effects (R package glmmTMB; 65 ).Poisson, negative binomial, or binomial distributions were assumed based on diagnostics of model residuals, which were assessed using R package DHARMa 66 .The drought-response strategy for each taxon was identified as resistant (no significant response to drought detected), sensitive (negative response), or opportunistic (positive response) using a significance level () of 0.05.Prior to statistical analysis, indices for each group (by drought-response strategy) were calculated as follows: for Commented [BKK10]: Do you mean rarefied?If so, consider using the word rarefied.
Commented [BKK11]: Don't need the semicolon here each OTU in a given group, its relative abundance in a given sample was standardized relative to its abundance across all samples; these standardized abundances were then summed across all OTUs in a given group resulting in one value per group per sample.
Structural equation modelling was used to investigate effects of historical management, drought, and soil properties on relative abundances of opportunistic, sensitive, and resistant taxa at the two sampling timepoints.Within-field reps were averaged prior to analysis (n = 180/3 = 60 per timepoint).We constructed an a priori model based on current knowledge of plant-soil-microbefunctioning interactions (see Fig. S5 and Supplemental Note 1) and tested whether the data fit these models using the standard modelling approach in the lavaan R package 67 .We created a proxy for soil properties using axis 1 scores from a non-metric multidimensional scaling plot that included total soil carbon, total nitrogen, and soil temperature (see Supplemental Note 1).We used multiple parameters including root mean square error of approximation (RMSEA), comparative fit index (CFI), and Standardized Root Mean Squared Residual (SRMR) to assess model fit.Reviewer #2: Remarks to the Author: Dominant taxa in soil microbial communities play outsized roles in ecosystem functioning.However, their capacities to resist and recover from climate extremes such as drought under different environmental contexts remain poorly studied.This manuscript entitled "Land management shapes drought responses of dominant soil microbial taxa across grasslands" by Lavallee et al. reports the responses of dominant bacteria and fungi immediately after drought and after a post-drought recovery period from an in situ experimental drought across 30 UK grassland sites representing a wide range of soil and climatic conditions and contrasting management intensities.The authors found that the majority of dominant bacterial and fungal taxa showed resistant or opportunistic drought strategies, while small proportions of dominant microbial taxa displayed sensitive strategies in response to drought.They also reported that intensive grassland management increased the proportion of dominant bacterial taxa with resistant and opportunistic strategies, but had the opposite impact on dominant fungal taxa.They highlighted that these links between grassland management and drought responses of dominant soil microbial taxa is a key step towards better predicting grassland ecosystem responses to drought.Overall, I think the results of this manuscript is very interesting and meaningful.However, I have several concerns about the experimental design and associated analyses: 1.It is hard to understand how the author can evaluate the resistance and resilience of dominant taxa in soil microbial communities only using data at two timepoints.Normally, long-term data from at least several timepoints before drought are needed to evaluate the microbial communities under the normal condition.Without this information, it is impossible to accurately evaluate microbial resistance and resilience to drought.Therefore, I don't think the data in this study can support the key message.2. The authors highlight their study is across grasslands in the title.However, it seems that they don't provide any information about how many types of grasslands are studied here, though they reports that this study is carried out in 15 sites and 30 paired fields.If all 15 sites are from the same kind of grassland, the generalizability of the findings is questionable.I suggest the authors to provide more information about the grasslands in this study.3. Line 408: the authors mention measurements of soil nematode communities and microarthropod communities, but no any results about them are reported in this manuscript.Why? 4. Line 463: Greengenes Release 13_5 is a very old version of reference database, and several new versions of Greengenes databases have been released in recent years.Thus, I suggest the authors to update their results by using the newest version of Greengenes.
All Reviewer comments are reproduced word-for-word below, with point-by-point responses in blue.

REVIEWER COMMENTS
Reviewer #1 (Remarks to the Author): I thoroughly enjoyed reviewing this manuscript.The authors did an excellent job with the writing.It is the most well-written manuscript I have reviewed.The authors provided a generally comprehensive description of the work.I appreciate the reasoning for the focus on dominant taxa.The takeaway that most of the dominant taxa from these soils exhibit resistant or opportunistic strategies in response to drought provides a foundation for some important theories in soil microbial ecology that have been hinted at in the literature for some time, but scarcely explicitly tested as the authors have done so here.I think this paper will help motivate other researchers in this field to make more of a point of differentiating between dominant and rare taxa and their respective roles in microbial processes and ecosystem functioning.I also appreciate the latitudinal gradient of the experimental design, which strengthens the inference power of these results and--as the authors state--make them more ecologically relevant.
I have provided minor comments in the attached word document with track changes, most of which are suggesting clarifications with phrasing or providing more detail.In particular, I would really like to see broader context added to the hypotheses and to expand on this in the Discussion.With papers like this that focus on soil microbial taxonomic composition, it's important to relay to the reader how microbial composition may influence ecosystem function.The authors have done a nice job with providing possible explanations for microbial responses to drought, land management, etc.Now they just need to bookend the story by providing some thoughts on how these microbial response strategies may affect larger scale ecosystem functions.I think the importance of this work would come through even more by making these small improvements.
We thank the reviewer for their kind words and appreciate their thoughtful review.We have copied the reviewer's comments and edits from the word document below, with point-by-point responses.This includes a similar comment to that in the final paragraph above, which we address below.Lines 1-2: Could you make this more descriptive by adding a colon?I want to know HOW drought shaped microbial responses.We are limited by the requirements of the journal to keep the title below 15 words and without punctuation and struggle to see how can include text to say how drought shaped microbial responses within this limit.We therefore are not able to accommodate this suggestion but do think that our current title captures the key general message of our paper.
Line 88: Even though you do so in the Methods, it would be helpful to briefly define the strategies here.I think's it's also worth explicitly differentiating between resistant and resilient because many people outside of this literature often use them interchangeably.This is a good point and have edited the text accordingly.Lines 82-89 now read: "Using an operational approach, we identified dominant microbial taxa and classified them into three broad drought-response strategies (i.e., resistant [no detectable response], opportunistic [positive response], or sensitive [negative response]) 14 .We examined the interacting effects of climate, soil properties, and historical grassland management on dominant microbial taxa by drought-response strategy immediately following the drought and after a 60-day post-drought period 23 , to capture both microbial resistance (lack of response to a perturbation) and resilience (recovery to an un-perturbed state) to drought 24,25 ." Line 91: It would be helpful to add broader context to the hypotheses.What would each of these hypotheses, or them collectively, indicate about microbial function under climate extremes if they were supported?Thank you for this great suggestion.We added a final paragraph to better meet the journal formatting requirements and now present brief findings and conclusions, including a sentence similar to what the reviewer has suggested above.The final paragraph of the introduction lines 98-108 now read as follows: "Our results show that most dominant soil microbial taxa were resistant to drought, as expected.We further show that intensive grassland management increases the proportion of dominant bacterial taxa that are resistant or opportunistic in the face of drought relative to those that are sensitive, and increases the proportion of taxa that are resilient relative to those that are not resilient.However, intensive management has the opposite effect on dominant fungal taxa, increasing the proportions of sensitive and non-resilient taxa.Our finding that land management shapes the drought-response strategies of dominant soil microbial taxa has important implications for microbial community structure and function.Intensive grassland management is known to broadly favour bacteria over fungi, impacting key functions including soil carbon and nitrogen cycling 25,26 ; our results suggest this pattern may be exacerbated as droughts become more frequent and intense with climate change." Line 116: It would be helpful to have bacteria and fungi labels at the top or bottom of these trees so that it's immediately obvious to the reader which is which.Also, I don't recall any Methods text that describes how the trees were made.We have added the labels to Figure 1 as suggested and added text to the Methods section describing how the plots were made (lines 491-492): "Plots showing circular representations of the taxonomic trees were created using the GraPhlAn software tool (https://huttenhower.sph.harvard.edu/graphlan/)." Line 120: delete "resistance" and change "tolerant" to "resistant" Done (now line 131) Line 122: delete "resilience" Done (now line 132) Lines 142-145: I would appreciate an Excel table of all dominant taxa, their full taxonomy, and response strategy.It's fine to not provide all this detail in the manuscript, but I think it should be made available.I'm curious (and I'm sure many other readers will be, too) to know which orders, families, etc. have resistant and sensitive taxa.This table was provided previously as an .RData object, but we have now also included it as a .csvfile along with the other data and code for this study, on figshare and at https://github.com/soilnerd/lavallee-2023-dom-micro-drought.
Lines 270-271: change wording to, "…opportunistic taxa to succeed under the drought treatment relative to other taxa.These opportunistic taxa…" Done (now lines 286-287) Lines 287-288: change wording to, "… which are thought to be comprised of mainly oligotrophs…" Done (now lines 303-304) Line 288: It would helpful to add in parentheses a brief description of oligotrophs as they relate to copiotrophs.Ex: generally have a slow growth strategy and thrive in nutrient-poor conditions Thank you for the suggestion.Lines 302-305 now read: "Further, Verrucomicrobia and Acidobacteria, which that are thought to be comprised of mainly oligotrophs (taxa that grow slowly and perform well under nutrient-poor conditions relative to copiotrophs) 21,34,35 , had the lowest proportions of drought-sensitive taxa that were resilient."Lines 361-363: You've done a great job with the discussion, and the cherry on top would be to expand on this sentence a bit more-like I suggested in the hypotheses section of the Introduction.Just providing a few sentences about how these microbial strategy responses to drought and land management may impact particular ecosystem functions like carbon, nutrient cycling, etc.This would really help drive home the importance of this work.Thank you very much, and we appreciate the suggestion to strengthen the discussion.We have added text to lines 373-376 as follows: "Our results suggest the pattern of bacterial prevalence over fungi under intensive management may be reinforced or exacerbated as droughts become more frequent and intense with climate change, and potentially contribute to less efficient C and N cycling in these systems 26,27 ."Line 429: spell out "organic matter" Done (now line 449) Line 469: replace "resampled" with "rarified" Done (now line 489) Line 478: delete semicolon Done (now line 500) Lines 484-486: For clarification: were separate models run for each "dominant" OTU?I'm confused with the grouping described here.What is meant by "indices for each group"?This is a good point, and we agree that we were not adequately clear in our description of the statistics.We have therefore edited the text to clarify this point and in lines 495-510 to read: "All analyses were done separately for bacterial and fungal taxa in R version 4.0.2 64.We defined dominant taxa as those which were present across all 15 sites (management pairs) and represented the top 10% of taxa when ranked by relative abundance (rRNA reads).The response of each of these dominant taxa to drought treatment was identified using a generalized linear mixed model across all experimental plot pairs with drought treatment as a fixed effect, and region/site/field as nested random effects (R package glmmTMB 65 ).For each individual model, the appropriate distribution (poisson, negative binomial, or binomial) was assumed based on diagnostics of model residuals, which were assessed using R package DHARMa 66 .The droughtresponse strategy for each taxon was identified as resistant (no significant response to drought detected), sensitive (negative response), or opportunistic (positive response) using a significance level (α) of 0.05.Further statistical analysis was performed at the drought-response group level (i.e., resistant, opportunistic, sensitive, resilient, not resilient), for which group-level indices were calculated as follows: for each OTU in a given group, its relative abundance in a given sample was standardized relative to its abundance across all samples; these standardized abundances were then summed across all OTUs in a given group resulting in one value (index) per group per sample."Supplemental Material, Lines 86-88: I'm curious as to why pH and SWC were not also grouped in with C, N, texture, and soil temp or why each was not its own factor in the SEMs?I don't have much experience with running SEMs myself, but are you unintentionally overweighting pH and SWC in respect to the other edaphic variables by grouping them this way?This is a great question and appreciate the reviewer raising this point.We purposely kept soil pH and water content as individual variables in the SEM because soil water content is a reflection of the drought treatment relative to the control and is therefore important to explicitly represent.In contrast, soil pH is known to be one of the most important controls on soil microbial communities and is also managed directly in the intensive fields through liming.We also found support separating pH from the other soil properties in an early version of the SEM structure that included separate paths for each of the variables (but was not a better model in terms of explaining variance in microbial groups and was therefore not preferred relative to the final model).When modeled separately, pH consistently showed much larger standardized path coefficients than soil C, texture, and soil temperature (typically on the order of 2 -3x the magnitude), supporting the idea that it is an important variable for explaining microbial responses and should therefore ideally be modeled separately.We have added explanation to the Supplemental Material to clarify this point, in lines 96-99 as follows: "Two soil properties, soil water content (SWC) and pH, were not included in the "soil" variable because they were deemed important to model separately.This was done because both properties are of particular interest for this study: SWC is a reflection of the effect of the drought treatment relative to the control, and pH is known to be an important control on soil microbial communities and is also managed directly in the intensive fields." Reviewer #2 (Remarks to the Author): Dominant taxa in soil microbial communities play outsized roles in ecosystem functioning.However, their capacities to resist and recover from climate extremes such as drought under different environmental contexts remain poorly studied.This manuscript entitled "Land management shapes drought responses of dominant soil microbial taxa across grasslands" by Lavallee et al. reports the responses of dominant bacteria and fungi immediately after drought and after a post-drought recovery period from an in situ experimental drought across 30 UK grassland sites representing a wide range of soil and climatic conditions and contrasting management intensities.The authors found that the majority of dominant bacterial and fungal taxa showed resistant or opportunistic drought strategies, while small proportions of dominant microbial taxa displayed sensitive strategies in response to drought.They also reported that intensive grassland management increased the proportion of dominant bacterial taxa with resistant and opportunistic strategies, but had the opposite impact on dominant fungal taxa.They highlighted that these links between grassland management and drought responses of dominant soil microbial taxa is a key step towards better predicting grassland ecosystem responses to drought.Overall, I think the results of this manuscript is very interesting and meaningful.However, I have several concerns about the experimental design and associated analyses: 1.It is hard to understand how the author can evaluate the resistance and resilience of dominant taxa in soil microbial communities only using data at two timepoints.Normally, long-term data from at least several timepoints before drought are needed to evaluate the microbial communities under the normal condition.Without this information, it is impossible to accurately evaluate microbial resistance and resilience to drought.Therefore, I don't think the data in this study can support the key message.
We appreciate this point and agree that having long-term data would be ideal to understand variation in microbial communities through time, however, we believe the data presented in our study support the key message.Because microbial communities in soil can change dramatically through time, we designed the experiment to compare droughted plots to ambient control plots at each timepoint (and not between timepoints), as commonly done in experiments that measure resistance and resilience of microbial communities and their functioning (de Vries et al., 2012; Ingrisch and Bahn, 2018; Yi and Jackson, 2021).We purposely avoided comparisons of the droughted plots through time as we expected differences in environmental conditions and plant biomass over the season to contribute to changes over time in the droughted plots, which would have made it difficult to distinguish drought impacts from background temporal variation.The ambient control plots fluctuated through time and allowed us to capture that background temporal variation.We therefore maintain that our approach allows us to investigate resistance and resilience of microbial communities in the droughted plots relative to their paired ambient controls at the respective timepoints.However, to clarify this point and address the reviewer's point, we have edited the Methods text to clarify this aspect of the experimental design in lines 413-419: "In total, there were 90 pairs of droughted and ambient control plots, and the three within-field replicates of each were treated appropriately in all statistical models by either including site and field as random effects or by aggregating the data at the field scale where random effects could not be modelled.At the end of the drought period, drought shelters were removed and an initial ("day 0") sampling and measurement of soil functions (in both drought and control plots) was carried out to assess the impact of the drought relative to the ambient control conditions." Further, to support our assumption that the ambient control plots are representative of the study sites and comparable to the droughted plots in terms of key properties that are known to explain spatial variation in microbial communities (soil C and N, pH, soil temperature, soil texture), we have provided below a formal comparison of control and droughted plots with respect to those properties to show that they are similar.The PCA plot shows overlap between control (C) and drought (D) plots across sites, and the Adonis output confirms no significant differences between control and drought plots ("treatment" factor) when accounting for the hierarchical experimental design structure.

Figure 2 .
Figure 2. Structural equation models (SEMs) of dominant bacteria and fungi at the two time points in this study: immediately following the drought treatment (day 0), and after the 60-day post-drought recovery period.The "soil" variable is a composite representation of soil C, N, texture, and temperature.SWC is soil water content by volume.The drought-response strategy (opportunistic, sensitive, resistant) of each OTU was determined by the drought treatment effect using linear mixed models.Arrow (path) thickness corresponds to the standardized coefficients, also written next to their respective paths.Paths of less interest are shaded grey to improve overall readability.Solid arrows indicate p value < 0.05; path coefficients with p values > 0.05 are not shown.See Fig. S5 and Supplemental Note 1 for more detail.

Figure 2 .
Figure 2. Structural equation models (SEMs) of dominant bacteria and fungi at the two time points in this study: immediately following the drought treatment (day 0), and after the 60-day post-drought recovery period.The "soil" variable is a composite representation of soil C, N, texture, and temperature.SWC is soil water content by volume.The drought-response strategy (opportunistic, sensitive, resistant) of each OTU was determined by the drought treatment effect using linear mixed models.Arrow (path) thickness corresponds to the standardized coefficients, also written next to their respective paths.Paths of less interest are shaded grey to improve overall readability.Solid arrows indicate p value < 0.05; path coefficients with p values > 0.05 are not shown.See Fig. S5 and Supplemental Note 1 for more detail.

Figure 4 .
Figure 4. Log response ratio of key variables related to grassland intensification.Log response ratio is calculated as the natural log of the ratio of the value of a given variable in an intensively managed grassland to the corresponding value in the paired extensively managed field.Fifteen pairs of intensive and extensive grasslands, 5 per region, are shown here with each point representing the log ratio of within-field means for one pair (site).

Figure S1 .
Figure S1.Map showing site locations, with detail for each of the three regions (Devon, North Yorkshire, Aberdeenshire).Each point represents one site consisting of two paired fields with contrasting management (extensive, intensive).

Figure S2 .
Figure S2.Effects of drought and grassland management on soil moisture (a), ecosystem respiration (b), aboveground plant biomass (c), and microbial biomass (d), measured immediately following removal of drought shelters.P values from linear mixed effect models for drought (Dr), management (Ma), and their interactions (Dr*Ma) are given.

Figure S3 .
Figure S3.Constantly-monitored moisture probe data for one drought-control pair in each of the three regions shows reductions in soil moisture for the duration of the experimental drought period.
Figure S4.Relationships between soil pH and standardized relative abundances of resistant (a) and resilient (b) bacterial taxa and resistant (c) and resilient (d) fungal taxa across all samples collected in this experiment.Lines are polynomial fits of the data produced with the ggplot2 package in R, with corresponding fit equations and multiple R 2 values.

Line 310 :
These ratios are usually expressed as fungi:bacteria.Thank you for catching this, it has been corrected.(Now line 326) Lines 312-313: change wording to, "… as other studies have found trade-offs…" Done (now line 329) Line 350: change wording to, "…most of the dominant soil…" Done (now line 365)

Table S1 .
Characteristics of the grassland sites used in this study.Each site consists of paired pastures under contrasting management 32 ("extensive" or "intensive").Paired of fields at each site are adjacent or located < 0.5 km apart.33

Table S2 .
Count and % of dominant bacterial (16S) and fungal (ITS) OTUs classified under each drought response strategy across all sites.Values in parenthesis are the number or percentage (of total) of opportunistic or sensitive OTUs classified as resilient.

Table S3 .
Results of perMANOVA analysis of Bray-Curtis dissimilarities using all relative abundance data for a) bacterial (16S) and 55 b) fungal (ITS) genes in relation to drought treatment, region, management and their interactions.Df = degrees of freedom; 56 SumsOfSqs = sums of squares; F.Model = F value by permutation; p values based on 999 permutations (lowest p-value possible is 57 0.001).Asterisks indicate significance at  = 0.05.Due to the structure of the model call (stratification at field level), terms that do not 58 include drought (gray text) are not accurately represented and should be ignored.